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Статті в журналах з теми "Software algorithm"

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Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 травня 2022

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1

Sharma, Divya, and Shikha Lohchab. "Search based Software Modularization Using Evolution Algorithm." NeuroQuantology 20, no. 5 (May 18, 2022): 822–31. http://dx.doi.org/10.14704/nq.2022.20.5.nq22240.

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Анотація:

To comprehend a Software system, Software modularization strategies are used. The goal of modularization is to break down a software system into meaningful and intelligible sub-systems from its source-code (modules). Because software classification modularization is an NP-hard task, evolutionary methods produce better modularization quality rather than avaricious algorithms. All available transformative techniques for software modularization only take into account structural aspects reliant on programming language syntax. Because most computer languages lack a mechanism for extracting structural characteristics, they cannot be modularized. A novel heuristic is proposed in this work. with several objectives that accomplishes both in order to lead optimization algorithms towards a proper decomposition of software systems automatically, structural (e.g.; calling dependence and in-heritance dependency) and non- structural (e.g.; semantics in code comments and identifier names) aspects are used. It is analyzed using 3 optimization plans, viz; global-based-search, combining global and local search, and Estimation of Distribution (EoD) to upgrade it. According to outcomes on Mozilla Firefox, suggested optimization algorithm based on EoD and the newly developed MOF function exceed those so it use structural-based objective functions in finding more understandable modules, as well as guiding the optimization procedure. In the lack of a unique concept, structure, the original design can be identified by using the source code of the disturbed software. Effective software maintenance depends on the concept of software system. One of most powerful techniques in software clustering is the ability to divide enormous Software systems into workable subsystems with modules of identical characteristics, thereby reducing the complexity of the system. A metaheuristic optimization imperialist competitive system has emerged algorithm, genetic algorithm, and their combination is examined for software clustering in this paper. When it comes to value, of clustering, the number of epochs required for convergence, and the standard unconventionality found at the end of repeated application of these algorithms, it appears that recursive application is the most effective for achieving the best performance.

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2

RAJALAKSHMI.M, RAJALAKSHMI M. "Software System Re-Modularization using Interactive Genetic Algorithm." Paripex - Indian Journal Of Research 3, no. 4 (January 15, 2012): 105–7. http://dx.doi.org/10.15373/22501991/apr2014/32.

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3

Hutagalung, Cerlinto. "Banker Algorithm Simulation Software." Instal : Jurnal Komputer 12, no. 02 (October 26, 2021): 61–68. http://dx.doi.org/10.54209/jurnalkomputer.v12i02.22.

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Анотація:

Banker's algorithm is an algorithm that models a bank in a small town dealing with a set of customers. This banker algorithm is used to deal with queuing problems in banking. In this case, one of them is how to simulate queues in banking. In this study, the design and manufacture of simulation software is used to help simulate whether a system is in a safe state or an unsafe state, in a safe condition the process is continued but if the process is unsafe the process is delayed until the system is in a safe state. The result of this research is a banker algorithm simulation software that models a banker who is dealing with a group of customers in a bank.

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4

ZOMORODIAN, AFRA, and HERBERT EDELSBRUNNER. "FAST SOFTWARE FOR BOX INTERSECTIONS." International Journal of Computational Geometry & Applications 12, no. 01n02 (February 2002): 143–72. http://dx.doi.org/10.1142/s0218195902000785.

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Анотація:

We present fast implementations of a hybrid algorithm for reporting box and cube intersections. Our algorithm initially takes a divide-and-conquer approach and switches to simpler algorithms for low numbers of boxes. We use our implementations as engines to solve problems about geometric primitives. We look at two such problems in the category of quality analysis of surface triangulations.

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5

LAVRENCHUK, Svitlana, Nina ZDOLBITSKA, and Nadiia KHAMULA. "SOFTWARE COMPLEX FOR GRAPH ALGORITHMS VISUALIZATION." Herald of Khmelnytskyi National University 303, no. 6 (December 2021): 81–85. http://dx.doi.org/10.31891/2307-5732-2021-303-6-81-85.

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Анотація:

Algorithms on graphs represented by graphical structures are offered. The software complex has a modular web interface. A representative graph is implemented as a set of vertices in the form of numbered circles and links between them (graphic image); using dynamically linked lists (adjacency lists); using an adjacency matrix. The project of this project allows the use of interactive algorithms for step-by-step calculations and algorithms on graphical images to obtain the necessary research results and competencies in the use of discrete structures. The project was implemented using HTML, CSS, JavaScript, which allows visualizing the application and interactively working with algorithms on graphs represented by different data structures. Graphics File Algorithm Programming provides web-based and interactive algorithms created by the used DHTML itself, creating a software project in the form of a site. Each page is dedicated to a separate algorithm and structurally consists of a header, container, footer. The website design uses HTML and cascading CSS stylesheets, to create an interactive parsing process and to transform methods in graphic files – based on JavaScript, which allows third-party scripts to be processed and rendered. The user can vibrate the image type (for orientation), the number of nodes, the presentation method, generate this graph, indicate the starting point for starting the search algorithm, observe the operational operation of the algorithm. The user can adjust the animation speed. The development of a set of programs is meant for interactive demonstration and visualization of the operation of algorithms in the study of graph theory.

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6

Kim, Taekhee, Kwonyong Lee, Junhee Lee, Sungyong Park, Young Hwa Kim, and Byungjoon Lee. "A Dynamic Timeout Control Algorithm in Software Defined Networks." International Journal of Future Computer and Communication 3, no. 5 (October 2014): 331–36. http://dx.doi.org/10.7763/ijfcc.2014.v3.321.

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7

Kotyk, Vladyslav, and Oksana Lashko. "Software Implementation of Gesture Recognition Algorithm Using Computer Vision." Advances in Cyber-Physical Systems 6, no. 1 (January 23, 2021): 21–26. http://dx.doi.org/10.23939/acps2021.01.021.

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This paper examines the main methods and principles of image formation, display of the sign language recognition algorithm using computer vision to improve communication between people with hearing and speech impairments. This algorithm allows to effectively recognize gestures and display information in the form of labels. A system that includes the main modules for implementing this algorithm has been designed. The modules include the implementation of perception, transformation and image processing, the creation of a neural network using artificial intelligence tools to train a model for predicting input gesture labels. The aim of this work is to create a full-fledged program for implementing a real-time gesture recognition algorithm using computer vision and machine learning.

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8

Jayasudha, R., S. Subramanian, and L. Sivakumar. "Genetic Algorithm and PSO Based Intelligent Software Reuse." Applied Mechanics and Materials 573 (June 2014): 612–17. http://dx.doi.org/10.4028/www.scientific.net/amm.573.612.

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Анотація:

Software Reuse can improve the development time, cost and quality of Software artifacts. The Storage of artifacts plays an important role of easy retrieval of the needed components according to the requirement. In this paper a great measure has been taken for the retrieval of relevant component from the Ontology based repository. Two famous evolutionary algorithms Genetic Algorithm and Particle Swarm Optimization algorithm were used for extraction of needed component. These two algorithms are separately used for component retrieval. Genetic Algorithm in Component Retrieval is best suited if the repository has more number of relevant components. PSO for Component search is best suited if the query is highly refined to get more relevant document. PSO is used for the mainly query expansion. These two methods are combined first the retrieved set of component is organized with the help of GA and PSO for best query expansion. Thus these two methods are combined for best precision and retrieval time for different sets of requirement query

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9

YAMAZAKI, Kazuo. "PID digital software control algorithm." Journal of the Robotics Society of Japan 7, no. 3 (1989): 218–24. http://dx.doi.org/10.7210/jrsj.7.3_218.

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10

Rogaway, Phillip, and Don Coppersmith. "A Software-Optimized Encryption Algorithm." Journal of Cryptology 11, no. 4 (September 1998): 273–87. http://dx.doi.org/10.1007/s001459900048.

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11

Chatain, Peter, Rocky Garg, and Lauren Tompkins. "Evolutionary Algorithms for Tracking Algorithm Parameter Optimization." EPJ Web of Conferences 251 (2021): 03071. http://dx.doi.org/10.1051/epjconf/202125103071.

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Анотація:

The reconstruction of charged particle trajectories, known as tracking, is one of the most complex and CPU consuming parts of event processing in high energy particle physics experiments. The most widely used and best performing tracking algorithms require significant geometry-specific tuning of the algorithm parameters to achieve best results. In this paper, we demonstrate the usage of machine learning techniques, particularly evolutionary algorithms, to find high performing configurations for the first step of tracking, called track seeding. We use a track seeding algorithm from the software framework A Common Tracking Software (ACTS). ACTS aims to provide an experimentindependent and framework-independent tracking software designed for modern computing architectures. We show that our optimization algorithms find highly performing configurations in ACTS without hand-tuning. These techniques can be applied to other reconstruction tasks, improving performance and reducing the need for laborious hand-tuning of parameters.

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12

Yang, Ximin, Deqiang Wang, Wei Feng, Jingjing Wu, and Wan Tang. "Cryptographic Algorithm Invocation Based on Software-Defined Everything in IPsec." Wireless Communications and Mobile Computing 2018 (July 2, 2018): 1–11. http://dx.doi.org/10.1155/2018/8728424.

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Анотація:

IPsec was initially developed for IPv6 to ensure the communication security. With the development of Internet of Things (IoT) and the mounting importance of network security, increasing numbers of applications require IPsec to support the customized definition of cryptographic algorithms and to provide flexible invocation of these algorithms. To address this issue, an invocation mechanism for cryptographic algorithms is proposed in this paper and applied to IPsec, entitled Free to Add (FTA), based on the concept of software-defined everything. Using the idea of interface opening, the addition of a new cryptographic algorithm and updating of the existing algorithms in the algorithm library both can be achieved through the opening interfaces provided by FTA. Switching the cryptographic algorithm to be used in the FTA framework can avoid the unnecessary consumption. Besides, using the subalgorithm interface and algorithm-control interface designed here, FTA provides several software-defined invocation modes (e.g., combination and switching according to the control instruction sent by the control program) to implement hybrid encryptions or change the cryptographic algorithms for communication. Finally, the feasibility and availability of the proposed FTA mechanism are evaluated by StrongSwan.

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13

Yang, Shun Kun, and Fu Ping Zeng. "Improved Genetic Algorithms for Software Testing Cases Generation." Applied Mechanics and Materials 380-384 (August 2013): 1464–68. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1464.

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Анотація:

In order to realize the adaptive Genetic Algorithms to balance the contradiction between algorithm convergence rate and algorithm accuracy for automatic generation of software testing cases, improved Genetic Algorithms is proposed for different aspects. Orthogonal method and Equivalence partitioning are employed together to make the initial testing population more effective with more reasonable coverage; Genetic operators of Crossover and Mutation is defined adaptively by the dynamic adjustment according to multi-objective Fitness function, which can guide the testing process more properly and realize the biggest testing coverage to find more defects as far as possible. Finally, the improved Genetic Algorithm are compared and analyzed by testing one benchmark program to verify its feasibility and effectiveness.

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14

Gupta, Sachin, and Vinish Kumar. "Proposed Algorithm using WARE for the Elicitation of Software Requirements." International Journal of Engineering and Technology 3, no. 3 (2011): 319–22. http://dx.doi.org/10.7763/ijet.2011.v3.245.

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15

BEREŽNÝ, Štefan, Ján BUŠA, and Michal STAŠ. "Software Solution of the Algorithm of the Cyclic-Order Graph." Acta Electrotechnica et Informatica 18, no. 1 (March 1, 2018): 3–10. http://dx.doi.org/10.15546/aeei-2018-0001.

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16

Yang, L., B. F. Jones, and S. H. Yang. "Genetic algorithm based software integration with minimum software risk." Information and Software Technology 48, no. 3 (March 2006): 133–41. http://dx.doi.org/10.1016/j.infsof.2005.03.005.

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17

Deghbouch, Hicham, and Fatima Debbat. "Hybrid Bees Algorithm with Grasshopper Optimization Algorithm for Optimal Deployment of Wireless Sensor Networks." Inteligencia Artificial 24, no. 67 (February 20, 2021): 18–35. http://dx.doi.org/10.4114/intartif.vol24iss67pp18-35.

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Анотація:

This work addresses the deployment problem in Wireless Sensor Networks (WSNs) by hybridizing two metaheuristics, namely the Bees Algorithm (BA) and the Grasshopper Optimization Algorithm (GOA). The BA is an optimization algorithm that demonstrated promising results in solving many engineering problems. However, the local search process of BA lacks efficient exploitation due to the random assignment of search agents inside the neighborhoods, which weakens the algorithmâ€™s accuracy and results in slow convergence especially when solving higher dimension problems. To alleviate this shortcoming, this paper proposes a hybrid algorithm that utilizes the strength of the GOA to enhance the exploitation phase of the BA. To prove the effectiveness of the proposed algorithm, it is applied for WSNs deployment optimization with various deployment settings. Results demonstrate that the proposed hybrid algorithm can optimize the deployment of WSN and outperforms the state-of-the-art algorithms in terms of coverage, overlapping area, average moving distance, and energy consumption.

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18

Panteleev, A. V., and I. A. Belyakov. "Developing Software of Global Optimization Method Based on Grey Wolf Optimizer." Моделирование и анализ данных 11, no. 2 (2021): 59–73. http://dx.doi.org/10.17759/mda.2021110204.

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Анотація:

This article discusses the development of software that allows to simulate the algorithm of the “Grey Wolf Optimizer” method. This algorithm belongs to the class of metaheuristic algorithms that allow finding a global extremum on a set of admissible solutions. This algorithm is being the most efficiently used in a situation where the cost function is specified in the form of a black box. The algorithm belongs to both bioinspired algorithms and to the class of algorithms of Particle Swarm Optimization. To analyze the efficiency of the algorithm, software was created that allows to vary the parameters of the method. The article contains examples of the program’s work on various test functions. The purpose of the program is to collect and analyze statistical results, making possible to evaluate the final result. The program provides to build graphs that make it possible to make a more thorough assessment of the results obtained. The program has a step-by-step function that allows one to analyze the specifics and features of the algorithm. Analysis of statistical data provides more detailed selection of the parameters of the algorithm.

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19

Jeong, InKee. "Software Battle for Algorithm Education - Focused on Sorting Algorithm." Journal of The Korean Association of Information Education 22, no. 2 (April 30, 2018): 223–30. http://dx.doi.org/10.14352/jkaie.2018.22.2.223.

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20

Jain, Rachna, and Arun Sharma. "ASSESSING SOFTWARE RELIABILITY USING GENETIC ALGORITHMS." Journal of Engineering Research [TJER] 16, no. 1 (May 9, 2019): 11. http://dx.doi.org/10.24200/tjer.vol16iss1pp11-17.

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Анотація:

The role of software reliability and quality improvement is becoming more important than any other issues related to software development. To date, we have various techniques that give a prediction of software reliability like neural networks, fuzzy logic, and other evolutionary algorithms. A genetic algorithm has been explored for predicting software reliability. One of the important aspects of software quality is called software reliability, thus, software engineering is of a great place in the software industry. To increase the software reliability, it is mandatory that we must design a model that predicts the fault and error in the software program at early stages, rectify them and then increase the functionality of the program within a minimum time and in a low cost. There exist numerous algorithms that predict software errors such as the Genetic Algorithm, which has a very high ability to predict software bugs, failure and errors rather than any other algorithm. The main purpose of this paper is to predict software errors with so precise, less time-consuming and cost-effective methodology. The outcome of this research paper is showing that the rates of applied methods and strategies are more than 96 percent in ideal conditions.

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21

Izadkhah, Habib, and Mahjoubeh Tajgardan. "Information Theoretic Objective Function for Genetic Software Clustering." Proceedings 46, no. 1 (November 17, 2019): 18. http://dx.doi.org/10.3390/ecea-5-06681.

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Анотація:

Software clustering is usually used for program comprehension. Since it is considered to be the most crucial NP-complete problem, several genetic algorithms have been proposed to solve this problem. In the literature, there exist some objective functions (i.e., fitness functions) which are used by genetic algorithms for clustering. These objective functions determine the quality of each clustering obtained in the evolutionary process of the genetic algorithm in terms of cohesion and coupling. The major drawbacks of these objective functions are the inability to (1) consider utility artifacts, and (2) to apply to another software graph such as artifact feature dependency graph. To overcome the existing objective functions’ limitations, this paper presents a new objective function. The new objective function is based on information theory, aiming to produce a clustering in which information loss is minimized. For applying the new proposed objective function, we have developed a genetic algorithm aiming to maximize the proposed objective function. The proposed genetic algorithm, named ILOF, has been compared to that of some other well-known genetic algorithms. The results obtained confirm the high performance of the proposed algorithm in solving nine software systems. The performance achieved is quite satisfactory and promising for the tested benchmarks.

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22

Prohorenko, A., and P. Dumenko. "Software Algorithm Synthesis for Diesel Electronic Control Unit." Latvian Journal of Physics and Technical Sciences 55, no. 3 (June 1, 2018): 16–26. http://dx.doi.org/10.2478/lpts-2018-0017.

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Анотація:

Abstract Nowadays global engine construction gets significant progress at a technological level, but specified manufacturers do not release any information about the composition, the structure of the algorithms and the software used by their equipment. It is possible to obtain information only fragmentary and, for example, the description of the electronic control unit algorithm is completely missing. This is a barrier for small companies to improve and adjust existing engines for specific purposes. The present paper describes and develops algorithm synthesis for an electronic diesel engine regulator. Mathe-matical modelling of the automatic control system has been carried out within the framework of the research. The results of the research have demonstrated the efficiency and sustainability of automatic electronic control system using the proposed algorithm.

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23

Deorowicz, Sebastian. "Second step algorithms in the Burrows-Wheeler compression algorithm." Software: Practice and Experience 32, no. 2 (2002): 99–111. http://dx.doi.org/10.1002/spe.426.

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24

Mansouri, Taha, Ahad Zare Ravasan, and Mohammad Reza Gholamian. "A Novel Hybrid Algorithm Based on K-Means and Evolutionary Computations for Real Time Clustering." International Journal of Data Warehousing and Mining 10, no. 3 (July 2014): 1–14. http://dx.doi.org/10.4018/ijdwm.2014070101.

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Анотація:

One of the most widely used algorithms to solve clustering problems is the K-means. Despite of the algorithm's timely performance to find a fairly good solution, it shows some drawbacks like its dependence on initial conditions and trapping in local minima. This paper proposes a novel hybrid algorithm, comprised of K-means and a variation operator inspired by mutation in evolutionary algorithms, called Noisy K-means Algorithm (NKA). Previous research used K-means as one of the genetic operators in Genetic Algorithms. However, the proposed NKA is a kind of individual based algorithm that combines advantages of both K-means and mutation. As a result, proposed NKA algorithm has the advantage of faster convergence time, while escaping from local optima. In this algorithm, a probability function is utilized which adaptively tunes the rate of mutation. Furthermore, a special mutation operator is used to guide the search process according to the algorithm performance. Finally, the proposed algorithm is compared with the classical K-means, SOM Neural Network, Tabu Search and Genetic Algorithm in a given set of data. Simulation results statistically demonstrate that NKA out-performs all others and it is prominently prone to real time clustering.

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25

Oleshchenko, L. M., and O. О. Lysenko. "SOFTWARE METHOD FOR CLUSTERING SOFTWARE TESTING REPORTS USING KNN ALGORITHM." Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences, no. 4 (2020): 106. http://dx.doi.org/10.32838/2663-5941/2020.4/15.

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26

Papamanthou, Charalampos, Konstantinos Paparrizos, and Nikolaos Samaras. "A parametric visualization software for the assignment problem." Yugoslav Journal of Operations Research 15, no. 1 (2005): 147–58. http://dx.doi.org/10.2298/yjor0501147p.

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Анотація:

In this paper we present a parametric visualization software used to assist the teaching of the Network Primal Simplex Algorithm for the assignment problem (AP). The assignment problem is a special case of the balanced transportation problem. The main functions of the algorithm and design techniques are also presented. Through this process, we aim to underline the importance and necessity of using such educational methods in order to improve the teaching of Computer Algorithms.

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27

Li, Zhen, Tong Li, YuMei Wu, Liu Yang, Hong Miao, and DongSheng Wang. "Software Defect Prediction Based on Hybrid Swarm Intelligence and Deep Learning." Computational Intelligence and Neuroscience 2021 (December 28, 2021): 1–17. http://dx.doi.org/10.1155/2021/4997459.

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Анотація:

In order to improve software quality and testing efficiency, this paper implements the prediction of software defects based on deep learning. According to the respective advantages and disadvantages of the particle swarm algorithm and the wolf swarm algorithm, the two algorithms are mixed to realize the complementary advantages of the algorithms. At the same time, the hybrid algorithm is used in the search of model hyperparameter optimization, the loss function of the model is used as the fitness function, and the collaborative search ability of the swarm intelligence population is used to find the global optimal solution in multiple local solution spaces. Through the analysis of the experimental results of six data sets, compared with the traditional hyperparameter optimization method and a single swarm intelligence algorithm, the model using the hybrid algorithm has higher and better indicators. And, under the processing of the autoencoder, the performance of the model has been further improved.

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28

Zhang, Tao, Changfu Yang, and Xin Zhao. "Using Improved Brainstorm Optimization Algorithm for Hardware/Software Partitioning." Applied Sciences 9, no. 5 (February 28, 2019): 866. http://dx.doi.org/10.3390/app9050866.

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Анотація:

Today, more and more complex tasks are emerging. To finish these tasks within a reasonable time, using the complex embedded system which has multiple processing units is necessary. Hardware/software partitioning is one of the key technologies in designing complex embedded systems, it is usually taken as an optimization problem and be solved with different optimization methods. Among the optimization methods, swarm intelligent (SI) algorithms are easily applied and have the advantages of strong robustness and excellent global search ability. Due to the high complexity of hardware/software partitioning problems, the SI algorithms are ideal methods to solve the problems. In this paper, a new SI algorithm, called brainstorm optimization (BSO), is applied to hardware/software partitioning. In order to improve the performance of the BSO, we analyzed its optimization process when solving the hardware/software partitioning problem and found the disadvantages in terms of the clustering method and the updating strategy. Then we proposed the improved brainstorm optimization (IBSO) which ameliorated the original clustering method by setting the cluster points and improved the updating strategy by decreasing the number of updated individuals in each iteration. Based on the simulation methods which are usually used to evaluate the performance of the hardware/software partitioning algorithms, we generated eight benchmarks which represent tasks with different scales to test the performance of IBSO, BSO, four original heuristic algorithms and two improved BSO. Simulation results show that the IBSO algorithm can achieve the solutions with the highest quality within the shortest running time among these algorithms.

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29

Hlubeňová, Jana, and Daniel Hlubeň. "Algorithm for Selection of Simulation Software." Advanced Materials Research 463-464 (February 2012): 1077–80. http://dx.doi.org/10.4028/www.scientific.net/amr.463-464.1077.

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Анотація:

A lot of performance products designed for the simulation of manufacturing systems is currently available on the market. Some of them are designed exclusively for logistics, others are designed to simulate the robotic workplace and some of them allow simulation the entire virtual enterprise from its logistics to the entire workplace connected to the real system. The article describes the algorithm for choosing the most suitable simulation program.

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30

Kumar B, Mari, Latha P, and Praynlin E. "SOFTWARE EFFORT ESTIMATION USING GENETIC ALGORITHM." International Journal on Information Sciences and Computing 8, no. 1 (2014): 9–16. http://dx.doi.org/10.18000/ijisac.50142.

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31

Pavanasam, Velayutham, and Chandrasekaran Subramaniam. "Metabolic Algorithm for Software Requirement Engineering." Advanced Materials Research 267 (June 2011): 639–44. http://dx.doi.org/10.4028/www.scientific.net/amr.267.639.

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Анотація:

The objective of this work is to apply metabolic algorithm to the various items involved during the software development process. The metabolic algorithm is introduced in the rewriting mechanism of membrane or P system considering many time varying functions. Rules for requirement evolution, reaction between items in the membrane, communications between data items, process speed-up and abort rule are being proposed. The metabolic algorithm is applied for the transformation of user requirements into system requirements which can be further segregated into functional as well as non-functional requirements. The requirement elicitation is illustrated and verified to obtain the most expected requirement objects using C# programming language.

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32

AHARA, Kazushi, and Yuhei YAMAZAKI. "Software and Algorithm of Drawing Surfaces." Interdisciplinary Information Sciences 9, no. 1 (2003): 157–74. http://dx.doi.org/10.4036/iis.2003.157.

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33

Carroll, Martin, and Barbara G. Ryder. "An incremental algorithm for software analysis." ACM SIGPLAN Notices 22, no. 1 (January 1987): 171–79. http://dx.doi.org/10.1145/390012.24228.

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34

Sharma, Shivani, Aman Kaushik, and Abhishek Tomar. "Software Cost Estimation using Hybrid Algorithm." International Journal of Engineering Trends and Technology 37, no. 2 (July 25, 2016): 62–71. http://dx.doi.org/10.14445/22315381/ijett-v37p212.

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35

Pogliano, Umberto, Jean-Pierre Braun, Bostjan Voljc, and Rado Lapuh. "Software Platform for PMU Algorithm Testing." IEEE Transactions on Instrumentation and Measurement 62, no. 6 (June 2013): 1400–1406. http://dx.doi.org/10.1109/tim.2013.2239051.

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36

Arora, Ishani, and Anju Saha. "Software fault prediction using firefly algorithm." International Journal of Intelligent Engineering Informatics 6, no. 3/4 (2018): 356. http://dx.doi.org/10.1504/ijiei.2018.091870.

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Arora, Ishani, and Anju Saha. "Software fault prediction using firefly algorithm." International Journal of Intelligent Engineering Informatics 6, no. 3/4 (2018): 356. http://dx.doi.org/10.1504/ijiei.2018.10013012.

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38

Taghipour, Mohammad. "Implementation of Software-Efficient DES Algorithm." Advances in Networks 3, no. 3 (2015): 7. http://dx.doi.org/10.11648/j.net.s.2015030301.12.

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39

Qin, Shengchao, Jifeng He, Zongyan Qiu, and Naixiao Zhang. "An algebraic hardware/software partitioning algorithm." Journal of Computer Science and Technology 17, no. 3 (May 2002): 284–94. http://dx.doi.org/10.1007/bf02947306.

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40

Yan, Yongquan, and Ping Guo. "Predicting Software Abnormal State by using Classification Algorithm." Journal of Database Management 27, no. 2 (April 2016): 49–65. http://dx.doi.org/10.4018/jdm.2016040103.

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Анотація:

Software aging, also called smooth degradation or chronics, has been observed in a long running software application, accompanied by performance degradation, hang/crash failures or both. The key for software aging problem is how to fast and accurately detect software aging occurrence, which is a hard work due to the long delay before aging appearance. In this paper, two problems about software aging prediction are solved, which are how to accurately find proper running software system variables to represent system state and how to predict software aging state in a running software system with a minor error rate. Firstly, the authors use proposed stepwise forward selection algorithm and stepwise backward selection algorithm to find a proper subset of variables set. Secondly, a classification algorithm is used to model software aging process. Lastly, t-test with k-fold cross validation is used to compare performance of two classification algorithms. In the experiments, the authors find that their proposed method is an efficient way to forecast software aging problems in advance.

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41

Mojsilović, Marija, Ivana Terzić, Snežana Gavrilović, and Goran Miodragović. "Carrier optimization using CAD software and biologically inspired algorithms." IMK-14 - Istrazivanje i razvoj 27, no. 1 (2021): 25–31. http://dx.doi.org/10.5937/imk2101025m.

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Анотація:

This paper presents a comparative analysis of the application of biologically inspired algorithms and methodologies in CAD software packages, for determining the optimal profile values in carriers with two independent variables. As an example of a biologically inspired algorithm to solve this optimization problem, the scroll algorithm was applied, while the SolidWorks software package was used as an example of CAD.

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42

Prajapati, Amarjeet, and Zong Woo Geem. "Harmony Search-Based Approach for Multi-Objective Software Architecture Reconstruction." Mathematics 8, no. 11 (October 31, 2020): 1906. http://dx.doi.org/10.3390/math8111906.

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Анотація:

The success of any software system highly depends on the quality of architectural design. It has been observed that over time, the quality of software architectural design gets degraded. The software system with poor architecture design is difficult to understand and maintain. To improve the architecture of a software system, multiple design goals or objectives (often conflicting) need to be optimized simultaneously. To address such types of multi-objective optimization problems a variety of metaheuristic-oriented computational intelligence algorithms have been proposed. In existing approaches, harmony search (HS) algorithm has been demonstrated as an effective approach for numerous types of complex optimization problems. Despite the successful application of the HS algorithm on different non-software engineering optimization problems, it gained little attention in the direction of architecture reconstruction problem. In this study, we customize the original HS algorithm and propose a multi-objective harmony search algorithm for software architecture reconstruction (MoHS-SAR). To demonstrate the effectiveness of the MoHS-SAR, it has been tested on seven object-oriented software projects and compared with the existing related multi-objective evolutionary algorithms in terms of different software architecture quality metrics and metaheuristic performance criteria. The experimental results show that the MoHS-SAR performs better compared to the other related multi-objective evolutionary algorithms.

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Li, Zhencong, Qin Yao, and Wanzhi Ma. "Matching Subsequence Music Retrieval in a Software Integration Environment." Complexity 2021 (May 22, 2021): 1–12. http://dx.doi.org/10.1155/2021/4300059.

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Анотація:

This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the fusion of GFCC features and rhythm features to form new features under the processing of principal component analysis (PCA) dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system.

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44

Azoulay, Rina, Esther David, Mireille Avigal, and Dorit Hutzler. "The Impact of Learning Software on Improving Reading Comprehension Skills." International Journal of e-Education, e-Business, e-Management and e-Learning 10, no. 3 (2020): 235–48. http://dx.doi.org/10.17706/ijeeee.2020.10.3.235-248.

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One of the challenges of an intelligent tutoring system (ITS) is adapting the difficulty level of the questions posed to the student to suit the student’s academic level. Our study examines the task of adjusting the system’s level of challenges to the level of the learner and addresses the questions of how best to do so and whether there is any benefit from such adjustment. To answer these questions, we developed reading comprehension courseware that includes three adaptive algorithms for adjusting the level of the questions presented to the students: the random selection algorithm, the Q-learning based algorithm, and the Bayesian inference algorithm. We conduct a real-world experiment in which real high school students used the courseware to improve their reading comprehension skills. In order to compare and evaluate the performance of the algorithms, the courseware used by each student utilized one of the three adaptive algorithm alternatives. Our results demonstrate that when considering all of the students, there was significant improvement (learning gain) using each of the methods.

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45

Popovic, Marko, Branislav Kordic, Miroslav Popovic, and Ilija Basicevic. "Online algorithms for scheduling transactions on python software transactional memory." Serbian Journal of Electrical Engineering 16, no. 1 (2019): 85–104. http://dx.doi.org/10.2298/sjee1901085p.

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Designing online transaction scheduling algorithms is challenging because one needs to reconcile three opposing requirements: (i) they should be fast, (ii) they should minimize make span and maximize throughput, and (iii) they should produce conflict-free transaction schedules. In this paper we present four online transaction scheduling algorithms, namely, RR, ETLB, AC, and AAC algorithm, we prove their correctness and time bounds, and we conduct a theoretical analysis of the transaction schedules they produce, using three different workloads (RDW, CFW, and WDW). Finally, we compare various features of the four algorithms. The results are as expected, as we go from RR, over ETLB and AC, to AAC algorithms, the quality of the resulting schedules increases at the cost of increase of algorithm?s time complexity.

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46

Al Qasem, Osama, and Mohammed Akour. "Software Fault Prediction Using Deep Learning Algorithms." International Journal of Open Source Software and Processes 10, no. 4 (October 2019): 1–19. http://dx.doi.org/10.4018/ijossp.2019100101.

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Анотація:

Software faults prediction (SFP) processes can be used for detecting faulty constructs at early stages of the development lifecycle, in addition to its being used in several phases of the development process. Machine learning (ML) is widely used in this area. One of the most promising subsets from ML is deep learning that achieves remarkable performance in various areas. Two deep learning algorithms are used in this paper, the Multi-layer perceptrons (MLPs) and Convolutional Neural Network (CNN). In order to evaluate the studied algorithms, four commonly used datasets from NASA are used i.e. (PC1, KC1, KC2 and CM1). The experiment results show how the CNN algorithm achieves prediction superiority of the MLP algorithm. The accuracy and detection rate measurements when using CNN has reached the standard ratio respectively as follows: PC1 97.7% - 73.9%, KC1 100% - 100%, KC2 99.3% - 99.2% and CM1 97.3% - 82.3%. This study provides promising results in using the deep learning for software fault prediction research.

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Alexandru, Curcă. "Implementing a Software Load Balancer with a Genetic Algorithm." Scientific Bulletin of Naval Academy XXIII, no. 2 (December 15, 2020): 177–84. http://dx.doi.org/10.21279/1454-864x-20-i2-024.

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Анотація:

In the context of network evolution, concepts like Software Defined Networking (SDN) and Network Functions Virtualisation (NFV) appeared on the market. Network virtualization permits the implementation of routers, switches and load balancers in software and separation of control plane and data plane brings easier configuration, implementation and scalability. The monolithic design of traditional network devices can be changed by implementing new algorithms which will improve the overall system performance. An example is our Software Load Balancer with a Genetic Algorithm. The code written in Python is functional through the POX Controller and the advantages of evolutionary algorithms make this implementation an innovative solution for dynamically modified topologies.

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Hussein, Wasim A., Shahnorbanun Sahran, and Siti Norul Huda Sheikh Abdullah. "Patch-Levy-based initialization algorithm for Bees Algorithm." Applied Soft Computing 23 (October 2014): 104–21. http://dx.doi.org/10.1016/j.asoc.2014.06.004.

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49

Gong, Chibing. "Dynamic Search Fireworks Algorithm with Adaptive Parameters." International Journal of Ambient Computing and Intelligence 11, no. 1 (January 2020): 115–35. http://dx.doi.org/10.4018/ijaci.2020010107.

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As a comparatively new algorithm of swarm intelligence, the dynamic search fireworks algorithm (dynFWA) imitates the explosion procedure of fireworks. With the goal of achieving global optimization and further boosting performance of dynFWA, adaptive parameters are added in this present study, called dynamic search fireworks algorithm with adaptive parameters (dynFWAAP). In this novel dynFWAAP, a self-adaptive method is used to tune the amplification coefficient Ca and the reduction coefficient Cr for fast convergence. To balance exploration and exploitation, the coefficient of amplitude α and the coefficient of sparks β are also adapted, and a new selection operator is proposed. Evaluated on twelve benchmark functions, it is evident from the experimental results that the dynFWAAP significantly outperformed the three variants of fireworks algorithms (FWA) based on solution accuracy and performed best in other four algorithms of swarm intelligence in terms of time cost and solution accuracy.

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Shu, Bo, and Xiao Jun Du. "Software Source Code Plagiarism and Direction Detection Based on PDG." Applied Mechanics and Materials 373-375 (August 2013): 1172–77. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1172.

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Анотація:

Because of the complexity of the software development, some software developers may plagiarize source code that comes from other projects or open source software in order to shorten development cycle. Usually the copyist would modify and disguise the source code copied to escape plagiarism detection. So far, most algorithms cant completely detect the source disguised by the copyist, especially cant exactly distinguish between the source code and the plagiaristic code. In this paper, we summarize and analyze the effect of disguised source to the detection process, design the strategy to remove the effect of disguised source, and propose a PDG-based software source code plagiarism detection algorithm. The algorithm can detect the existence of disguised source, so as to find out source code plagiarism. And we propose a heuristic rule to make the detection algorithm have the ability to give the plagiarism direction. Any existing algorithm does not have this function. We prove the availability of the algorithm by experiment.

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